Issue 6, 2019

Comprehensive analysis of the lncRNA-associated ceRNA network identifies neuroinflammation biomarkers for Alzheimer's disease

Abstract

Accumulating evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in Alzheimer's disease (AD). In this study, we constructed an AD-derived lncRNA-associated ceRNA network (LncACeNET) based on the ceRNA hypothesis and co-expressed correlation analysis of RNAs (miRNAs, mRNAs and lncRNAs) from AD patients. Based on this network, we preliminarily identified new potential AD biomarkers including hsa-miR-155-5p, CERS6-AS1, and CTB-89H12.4. The functional enrichment analysis demonstrated that these inferred biomarkers were significantly correlated with AD-related biological processes such as neuron projection development and neuron projection morphogenesis. Notably, lncRNA CTB-89H12.4 is significantly associated with “calcium ion-regulated exocytosis of neurotransmitter”, “chemical synaptic transmission”, “presynaptic membrane assembly”, “receptor localization to synapse”, and “learning”. This indicates the important role of CTB-89H12.4 as a promising target for AD therapy. Subsequently, we used the computational pipeline DTINet and discovered 19 lines of probable therapeutic relationships between FDA-approved drugs and CTB-89H12.4, which offered a new avenue to repurpose existing FDA-approved drugs for AD indication. Our study provides a new landscape for LncACeNET in AD, and will benefit mechanism study and new drug development for AD.

Graphical abstract: Comprehensive analysis of the lncRNA-associated ceRNA network identifies neuroinflammation biomarkers for Alzheimer's disease

Supplementary files

Article information

Article type
Research Article
Submitted
15 Aug 2019
Accepted
06 Nov 2019
First published
22 Nov 2019

Mol. Omics, 2019,15, 459-469

Comprehensive analysis of the lncRNA-associated ceRNA network identifies neuroinflammation biomarkers for Alzheimer's disease

Y. Zhou, Z. Xu, Y. Yu, J. Cao, Y. Qiao, H. Qiao and G. Suo, Mol. Omics, 2019, 15, 459 DOI: 10.1039/C9MO00129H

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